Key points are not available for this paper at this time.
Our project aims to overcome communication challenges faced by the deaf and mute community through the introduction of a novel Android application employing sophisticated machine learning techniques.This application marks a significant advancement in communication technology by offering real-time detection, translation, and synthesis of sign language gestures.By harnessing cutting-edge AI capabilities, our application not only interprets complex sign gestures but also seamlessly translates them into spoken language, facilitating smooth linguistic interaction.In addition to its core functionalities, the application offers interactive learning modules, personalized sign language recognition, and user profiles to enhance user engagement.By harnessing the power of artificial intelligence, this application not only empowers individuals with disabilities but also promotes inclusivity and understanding among diverse communities.With advanced sign language recognition technology, deaf users can effectively communicate using sign language, with the added option to translate it into text or speech for their conversational partners.For those unable to speak, the application features a robust text-to-speech system for converting typed messages into spoken words, enabling fluid communication.Furthermore, speech recognition capabilities allow individuals who cannot type to engage in interactive dialogue by transcribing their spoken words into text.The application prioritizes user data security and privacy through stringent security measures, ensuring a safe and trusted communication environment."Accessibility Redefined" transcends its role as a mere application; it serves as a comprehensive toolkit that empowers and enriches the lives of individuals facing hearing impairments and speech difficulties.By bridging communication barriers and offering multiple avenues for expressing and understanding language, this application sets a new standard for accessibility and inclusivity.
Pisal et al. (Sun,) studied this question.